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In portraits, eyeglasses may occlude facial regions and generate cast shadowson faces, which degrades the performance of many techniques like faceverification and expression recognition. Portrait eyeglasses removal iscritical in handling these problems. However, completely removing theeyeglasses is challenging because the lighting effects (e.g., cast shadows)caused by them are often complex. In this paper, we propose a novel frameworkto remove eyeglasses as well as their cast shadows from face images. The methodworks in a detect-then-remove manner, in which eyeglasses and cast shadows areboth detected and then removed from images. Due to the lack of paired data forsupervised training, we present a new synthetic portrait dataset with bothintermediate and final supervisions for both the detection and removal tasks.Furthermore, we apply a cross-domain technique to fill the gap between thesynthetic and real data. To the best of our knowledge, the proposed techniqueis the first to remove eyeglasses and their cast shadows simultaneously. Thecode and synthetic dataset are available athttps://github.com/StoryMY/take-off-eyeglasses.

Portrait Eyeglasses and Shadow Removal by Leveraging 3D Synthetic Data